Výsledky vyhledávání - "Jungermann, Felix"

Autor: Jungermann, Felix

In this paper we present the Information Extraction (IE)-plugin for the open source Data Mining (DM) software RapidMiner1 [Mierswa et al., 2006]. The IE-plugin can be seen as an interface between natural language and IE- or DM-methods, because it con

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______788::92deb9bddd82f65241c58dbabe508770
https://duepublico2.uni-due.de/receive/duepublico_mods_00037039

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About the exploration of data mining techniques using structured features for information extraction

Autor: Jungermann, Felix

The World Wide Web is a huge source of information. The amount of information being available in the World Wide Web becomes bigger and bigger every day. It is impossible to handle this amount of information by hand. Special techniques have to be used

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b967bd817a6934b795d841b428421595
http://hdl.handle.net/2003/29487

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Handling Tree-Structured Values in RapidMiner

Autor: Jungermann, Felix

Attribute value types play an important role in mostly every datamin- ing task. Most learners, for instance, are restricted to particular value types. The usage of such learners is just possible after special forms of preprocessing. RapidMiner most c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::231e95608dfe39dba30890d0d058242a

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Documentation of the Information Extraction Plugin for RapidMiner

Autor: Jungermann, Felix

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9c42c22334376a0d457451b0c18d66a
http://hdl.handle.net/2003/29317

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Towards Adjusting Mobile Devices To User's Behaviour

Autor: Fricke, Peter, Jungermann, Felix, Morik, Katharina, Piatkowski, Nico, Spinczyk, Olaf, Stolpe, Marco, Streicher, Jochen

Mobile devices are a special class of resource-constrained em- bedded devices. Computing power, memory, the available energy, and network bandwidth are often severely limited. These constrained re- sources require extensive optimization of a mobile s

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Tree Kernel Usage in Naive Bayes Classifiers

Autor: Jungermann, Felix

We present a novel approach in machine learning by combining naive Bayes classifiers with tree kernels. Tree kernel methods produce promising results in machine learning tasks containing treestructured attribute values. These kernel methods are used

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ba449f9491cf13b0e4c596a16dcfcd8
http://hdl.handle.net/2003/29316

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Providing Information by Resource- Constrained Data Analysis

The Collaborative Research Center SFB 876 (Providing Information by Resource-Constrained Data Analysis) brings together the research fields of data analysis (Data Mining, Knowledge Discovery in Data Bases, Machine Learning, Statistics) and embedded s

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Enhanced services for targeted information retrieval by event extraction and data mining

Autor: Jungermann, Felix, Morik, Katharina

Where Information Retrieval (IR) and Text Categorization delivers a set of (ranked) documents according to a query, users of large document collections would rather like to receive answers. Questionanswering from text has already been the goal of the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70d96b4486213449f53b63df26da414d
http://hdl.handle.net/2003/25864

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